In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based ...In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.展开更多
基于并联机构单一性能指标的多样性和各单一性能指标之间的非线性关系,将核主成分分析(Kernel Principal Component Analysis,KPCA)方法与误差反传播(Back Propagation,BP)神经网络技术相结合,建立一个对可完成不同工作任务的并联机构...基于并联机构单一性能指标的多样性和各单一性能指标之间的非线性关系,将核主成分分析(Kernel Principal Component Analysis,KPCA)方法与误差反传播(Back Propagation,BP)神经网络技术相结合,建立一个对可完成不同工作任务的并联机构进行综合性能评价的KPCA-BP神经网络模型。通过合理的系统抽样,利用KPCA对BP神经网络的输入数据进行预处理,既能处理各单一性能指标间的非线性关系,又能简化BP神经网络结构,加快网络学习速度,提高预测精度,进而提出一种基于多种单一性能指标的并联机构全局综合性能评价新方法,为并联机构工作任务优序关系研究提供科学的参考依据。展开更多
基金Supported by the National Natural Science Foundation of China(No.11072106,No.51005133 and No.51375009)
文摘In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.
文摘基于并联机构单一性能指标的多样性和各单一性能指标之间的非线性关系,将核主成分分析(Kernel Principal Component Analysis,KPCA)方法与误差反传播(Back Propagation,BP)神经网络技术相结合,建立一个对可完成不同工作任务的并联机构进行综合性能评价的KPCA-BP神经网络模型。通过合理的系统抽样,利用KPCA对BP神经网络的输入数据进行预处理,既能处理各单一性能指标间的非线性关系,又能简化BP神经网络结构,加快网络学习速度,提高预测精度,进而提出一种基于多种单一性能指标的并联机构全局综合性能评价新方法,为并联机构工作任务优序关系研究提供科学的参考依据。
